Design and Implementation of a Volumetric Merging Tool

Isabel Vidaurre-Gallart, A. Sújar, Marcos García
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Abstract

The study of the human brain is one of the biggest research challenges nowadays. Thanks to the impressive improvement in technology, great advances are being achieved in the study of the microanatomical structures of the neurons, which are the main nervous system processing cells. The study of those structures requires to capture high-resolution images. In such cases, due to the resolution required, processing of complete neurons is unfeasible. The purpose of this project is to provide the neuroscientists with a tool that allows them to visualize and reconstruct complete neurons from multiple high-resolution sections. To this end, we developed a tool capable of loading different volumetric data sets and merging them into a new volume. A rendering engine was designed to support several volumetric rendering modes. The graphical user interface allows the user to interact with the volumes in intuitive way and facilitates volume stitching task. Furthermore, the implementation makes use of GPU to improve the application. CCS Concepts •Computing methodologies → Volumetric models;
体积合并工具的设计与实现
对人类大脑的研究是当今最大的研究挑战之一。由于技术上令人印象深刻的进步,神经元的微观解剖结构的研究取得了巨大的进展,神经元是主要的神经系统处理细胞。对这些结构的研究需要捕捉高分辨率的图像。在这种情况下,由于需要分辨率,处理完整的神经元是不可行的。该项目的目的是为神经科学家提供一种工具,使他们能够从多个高分辨率的部分中可视化和重建完整的神经元。为此,我们开发了一种工具,能够加载不同的体积数据集并将它们合并到一个新的体积中。设计了一个渲染引擎来支持几种体渲染模式。图形用户界面允许用户以直观的方式与卷进行交互,方便了卷拼接任务。此外,该实现还利用了GPU来改进应用程序。•计算方法→体积模型;
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